code: def main():
      # Create experiment
      experiment.create(name="primer_ez")
      # Create configs
      conf = Configs()
      # Override configurations
      experiment.configs(
          conf,
          {
              # Use character level tokenizer
              "tokenizer": "character",
              # Prompt separator is blank
              "prompt_separator": "",
              # Starting prompt for sampling
              "prompt": "It is ",
              # Use Tiny Shakespeare dataset
              "text": "tiny_shakespeare",
              # Use a context size of $256$
              "seq_len": 256,
              # Train for $128$ epochs
              "epochs": 128,
              # Batch size $32$
              "batch_size": 32,
              # Switch between training and validation for $10$ times
              # per epoch
              "inner_iterations": 10,
              # Model size
              "d_model": 512,
              "transformer.ffn.d_ff": 2048,
              # Use Adam optimizer
              "optimizer.optimizer": "Adam",
              "optimizer.learning_rate": 2.5e-4,
              # ⭐️ Use [**squared ReLU**](index.html) activation in the feed forward network.
              #
              # *Replace this with `ReLU` for $ReLU$.*
              "transformer.ffn.activation": "SquaredReLU",
              # ⭐️ Use [**Multi-DConv-Head Attention**](index.html) for encoder attention.
              #
              # *Replace this with `mha` for original multi-head attention.*
              "transformer.encoder_attn": "MultiDConvHeadAttention",
          },
      )
  
      # Set models for saving and loading
      experiment.add_pytorch_models({"model": conf.model})
  
      # Start the experiment
      with experiment.start():
          # Run training
          conf.run()
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/transformers/primer_ez/experiment.py
imports: from labml import experiment
  from labml.configs import option
  from labml_nn.transformers import TransformerConfigs
  from labml_nn.transformers.basic.autoregressive_experiment import Configs
  from labml_nn.transformers.configs import FeedForwardConfigs
  from labml_nn.transformers.primer_ez import SquaredReLU
label_desc: Use image node_id 5 for calling a global function with example usage: main() without return types